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Measurement error in an independent variable is one reason why OLS estimates may not be consistent. However, as shown by Dagenais (1994), in some circumstances the OLS bias may be ameliorated somewhat given the presence of serially correlated disturbances, and OLS may prove superior to standard...
Persistent link: https://www.econbiz.de/10010608491
We suggest and compare different methods for estimating spatial autoregressive panel models with randomly missing data in the dependent variable. We start with a random effects model and then generalize the model by introducing the spatial Mundlak approach. A nonlinear least squares method is...
Persistent link: https://www.econbiz.de/10010664711
In this paper, we consider the Cox-type tests of non-nested hypotheses for spatial autoregressive (SAR) models with SAR disturbances. We formally derive the asymptotic distributions of the test statistics. In contrast to regression models, we show that the Cox-type and J-type tests for...
Persistent link: https://www.econbiz.de/10010666092
In this paper, we first generalize an approximate measure of spatial dependence, the APLE statistic (Li et al., 2007), to a spatial Durbin (SD) model. This generalized APLE takes into account exogenous variables directly and can be used to detect spatial dependence originating from either a...
Persistent link: https://www.econbiz.de/10010574119
Investments in transport infrastructure have been widely used by decision makers to encourage economic growth, particularly during periods of economic downturn. There has been extensive research on the linkage between transport infrastructure and economic performance since the late 1980s,...
Persistent link: https://www.econbiz.de/10010703147
Surveys of artists' location choices show that they disproportionately reside in large cities. This paper introduces a model that attempts to explain this urban preference. The model includes four factors: access to other artists; access to consumer demand; access to service jobs; and housing...
Persistent link: https://www.econbiz.de/10011052363
This paper uses Hierarchical Bayes Models to model and estimate spatial health effects in Germany. We combine rich individual-level household panel data from the German SOEP with administrative county-level data to estimate spatial county-level health dependencies. As dependent variable we use...
Persistent link: https://www.econbiz.de/10010478790
Researchers using directed network data to estimate peer effects must somehow handle unreciprocated nominations. To better understand how peer effects operate and how best to estimate their effects, this paper investigates how the reciprocation of friendship mediates peer effects. We begin by...
Persistent link: https://www.econbiz.de/10010931311
This paper proposes a spatial panel model for German matching functions to avoid possibly biased and inefficient estimates due to spatial dependence. We provide empirical evidence for the presence of spatial dependencies in matching data. Based on an official data set containing monthly...
Persistent link: https://www.econbiz.de/10010608479
Higher-order spatial econometric models that include more than one weights matrix have seen increasing use in the spatial econometrics literature. There are two distinct issues related to the specification of these extended models. The first issue is what form the higher-order spatial...
Persistent link: https://www.econbiz.de/10010608489